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Crypto-Analysis

Member of team:

Full name StudentID
Đoàn Ánh Dương 20127474

Project information

  • Environment using: min_ds-env.
  • External package:
    • Plotly: conda install plotly.

File Information

  • archive/: Folder contains original files (unchanged files). Source I found on Kaggle by Sudalai Rajkumar.
  • crypto_finance.csv: File combined from files in `archive/' directory.
  • description.txt: Describe the meaning of each column in dataset.
  • Final.ipynb: Source code of my project.
  • Final.html: html view for prevention.
  • Final.pdf: pdf view for prevention.
  • README.md: please read me.

About data

The dataset has one csv file for each currency. Price history is available on a daily basis from April 28, 2013. This dataset has the historical price information of some of the top crypto currencies by market capitalization, including Bitcoin, Etherium, Binance Coin,...

Unofficial information: Data Source is collected by scraping on coinmarketcap coin history.

The data is subjective...

Completion Progress

Journey

Pros:

  • learning new knowledges, like interactive charts, finance, basic statistics...
  • Understand clearly how strong pandas is,...
  • The way to convert jupyter notebook to pdf, which characteristics to analyze, clean and preprocess data, read docs,...
  • How to write *.md and git command.
  • Many things I faced to, but forgetting...
  • I found some other fields I'm interested in; exploring myself, not only dataset.

Cons:

  • The file size of *.ipynb is too large (~7MB) and I don't know the issues, how to optimize its capacity.
  • The knowledge is limitless, I need to learn more and more.
  • Many questions about crypto market, but I can't answer with these datasets: Distribution holders all over the world by each coin?, which coins have trust?...

Preference